We also evaluated object location performance of our network and compared it with other SOTA on the PASCAL VOC 2007 trainval set in Table REF  and Table REF . The proposed network reached the best localization performance in 4 of the 20 classes(aeroplane, bird, chair and train). our network respectively outperformed WSDDN[1]}, OICR[2]}, WSCDN[3]}, MELM[4]}, C-MIL[5]} and other approaches by 1.0% \(\sim \)  12.5%.
